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Phase-change memory emerges as a top contender for non-volatile data storage applications. We report here a systematic change in local structure and crystallization kinetics of binary GeTe thin films using temperature-dependent resistivity measurements, which offers single-stage crystallization at around 187 °C, corroborated with x-ray diffraction. Furthermore, the change in chemical bonding upon crystallization is determined through x-ray photoelectron spectroscopy core level spectra, which reveals the existence of Ge and Te components that align with the GeTe crystal structure. Also, an investigation was carried out employing a UV–Vis–NIR spectrophotometer to explore the evolution of optical bandgaps (E g) , Tauc parameter (B) representing the local disorder, and Urbach energy (E u) of the GeTe material, as it undergoes the transition from a disordered amorphous state to a crystalline state. As crystallization progresses, a consistent shift of E g from 0.92 to 0.70 eV corresponds to as-deposited amorphous at room temperature and crystalline at 250 °C, respectively. In addition, the reduction in E u (from 199.87 to 141.27 meV) and a sudden increase of B around crystallization temperature is observed upon increasing temperature, indicating direct observation of enhanced medium-range order and distortion in short-range order, respectively, in GeTe thin films, revealing improved structural and optical properties. These enhancements make the GeTe material ideal for data storage applications of phase-change memory for next-generation computing technology. [ABSTRACT FROM AUTHOR]

In this study, we integrated an Indium Gallium Zinc Oxide (IGZO) channel with a superlattice of HfO2/ZrO2 (HZO) under low-thermal-budget microwave annealing to produce nearly wake-up-free ferroelectric capacitors. To eliminate the impact of trap-charges during the atomic layer deposition process, we conducted H2 plasma treatment to eliminate leak defects induced by carbon contamination and maintain neutrality to achieve high-quality IGZO/HZO interfaces, confirmed by x-ray photoelectron spectroscopy. The H2 plasma treatment improved polarization (Pr) and coercive field (Ec), reaching 2Pr: 40 μC/cm2 and Ec: 2.33 MV/cm, enabling a low-power writing speed of 30 ns with eight states (three bits per cell). The defect engineering method ensures endurance of up to 108 cycles and retains ten-year data storage at 90 °C. This research provides a new avenue for improving emerging oxide interfaces controlled by ferroelectric polarization. [ABSTRACT FROM AUTHOR]

Resistive Random Access Memory (RRAM) is considered one of the most promising candidates for big data storage. By using atomic layer deposition and magnetron sputtering, HfO2 thin films were prepared on ITO first, which exhibited good resistive switching (RS) characteristics in the structure of Ag/HfO2/ITO. By analyzing the RS mechanism, it is found that both metal conductive filaments and oxygen vacancy conductive filaments coexisted and Sn ion in ITO can influence the retention of RRAM. Furthermore, a device in the structure of Ag/HfO2/Pt was proposed and prepared, which exhibited excellent RS characteristics, including an ultrahigh switching ratio averaging up to 108 and low operating voltage. It is concluded that the difference in the work function between the top and bottom electrodes contributes to improving the switching ratio, reducing the operating voltage. In addition, the Ag/HfO2/Pt device is similar to the Ag/HfO2-based threshold switching selector in the structure and in characteristics of high switching ratio, besides non-volatile memory. Hence, the device is functionally equivalent to the combination of an RRAM and a threshold switching selector. It is the potential way to replace the conventional 1S1R structure memory. [ABSTRACT FROM AUTHOR]

Ge2Sb2Se4Te1 (GSST) exhibits unprecedented broadband transparency over the infrared wavelength range and has emerged as a promising functional material in photonic applications that operate in the optical fiber telecommunication wavelength band. In this work, GSST and graphene oxide (GO) are integrated into an optical fiber link to achieve all-fiber non-volatile multilevel photonic memory. The GSST and GO (GSST-GO) duo-layer hybrid structure is sandwiched between two optical fiber ferrules, where the GO acts as a localized heat source to initiate the phase transition of GSST upon optical excitation. The GSST-GO-coated fiber exhibits a low insertion loss of 0.8 dB and a maximum readout contrast of about 32%, with at least five distinguished memory states. The response time of the device is measured in the range between 2.5 and 9.5 μs. This work serves as a proof of concept on implementing the GSST-GO duo-layer hybrid structure in optical fiber platform to realize all-fiber non-volatile multi-bit channel control or data storage. [ABSTRACT FROM AUTHOR]

We like and need Information and Communication Technologies (ICTs) for data processing. This is measurable in the exponential growth of data processed by ICT, e.g., ICT for cryptocurrency mining and search engines. So far, the energy demand for computing technology has increased by a factor of 1.38 every 10 years due to the exponentially increasing use of ICT systems as computing devices. Energy consumption of ICT systems is expected to rise from 1500 TWh (8% of global electricity consumption) in 2010 to 5700 TWh (14% of global electricity consumption) in 2030 [A. S. G. Andrae, Eng. Appl. Sci. Lett. 3, 19–31 (2020)]. A large part of this energy is required for the continuous data transfer between separated memory and processor units, which constitute the main components of ICT computing devices in von-Neumann architecture. This, at the same time, massively slows down the computing power of ICT systems in von-Neumann architecture. In addition, due to the increasing complexity of artificial intelligence (AI) compute algorithms, since 2010, the AI training compute time demand for computing technology has increased tenfold every year, for example, from 1 × 10−6 to 1 × 10+4 Petaflops/day in the period from 2010 to 2020 [J. Wang, see https://ark-invest.com/articles/analyst-research/ai-training/ for information about the cost to train an AI interference system (2020)]. It has been theoretically predicted that ICT systems in the neuromorphic computer architecture will circumvent all of this through the use of merged memory and processor units. However, the core hardware element for this has not yet been realized so far. In this work, we discuss the perspectives for non-volatile resistive switches with hysteretic memristance as the core hardware element for merged memory and processor units in neuromorphic computers. [ABSTRACT FROM AUTHOR]

Owing to their ability for fast switching and the large property contrast between the crystalline and amorphous states that permits multi-level data storage, in-memory computing and neuromorphic computing, the investigation of phase change materials (PCMs) remains a highly active field of research. Yet, the continuous increase in electrical resistance (called drift) observed in the amorphous phase has so far hindered the commercial implementation of multi-level data storage. It was recently shown that the resistance drift is caused by aging-induced structural relaxation of the glassy phase, which is accompanied by a simultaneous decrease in enthalpy and fictive temperature. This implies that resistance is related to enthalpy relaxation. While the resistance is known to drift even at room temperature and below, evidence for enthalpy relaxation at room temperature in amorphous PCMs is still missing. Here, we monitor changes in enthalpy induced by long-term room-temperature aging in a series of PCMs. Our results demonstrate the simultaneity of resistance drift and enthalpy relaxation at room temperature, and thus provide further insights into the mechanism of resistance drift and its possible remediation. [ABSTRACT FROM AUTHOR]

Core enterprises are entering into close collaborations with multi-level manufacturing service providers to create and share value. However, credible data sharing in collaborative manufacturing supply chains is rare, which can lead to uncontrollable production distortions and delayed operational adjustments. Driven by blockchain technology, this study proposes a systematic framework for credible manufacturing data sharing for a cross-enterprise collaborative manufacturing supply chain (CMSC). To develop the needed method, a blockchain network system with blockchain nodes, distributed ledger, and Raft-based distributed node ordering service system was first modelled. Then, two automatic data upload algorithms were studied to ensure the reliability of off-chain manufacturing data sources from core enterprises, suppliers, and customers. Then, two types of smart contracts were designed to ensure the standardisation and co-validation of manufacturing data storage and query processes in the blockchain network. A demonstrative case was studied to validate the proposed blockchain-based credible manufacturing data sharing method. The results show that our work is effective for credible data sharing in CMSC, which makes it easier for core enterprises to better operate the CMSC and further stimulate enterprises to create a credible social community. [ABSTRACT FROM AUTHOR]

Ferroelectrics and multiferroics have added flexibility in device design as they can couple with either electric or magnetic polarization. Here, we report a simple approach to observe ferroelectric and multiferroic behavior in BFO embedded Ti 3 C 2 T x MXene free standing film. Structural, morphological, optical and domain analyses were done using X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), Raman spectroscopy, and Piezoresponse Force Microscopy (PFM) respectively. The hysteresis polarization curves obtained at various frequencies, both with and without a static magnetic field, provide confirmation of the frequency-dependent ferroelectric behavior within BFO embedded Ti 3 C 2 T x MXene free standing film. Magneto-electric couplings have demonstrated the film's ability to manipulate electric polarization using a magnetic field. Recently, researchers have unveiled ferroelectric properties in Ti 3 C 2 T x MXene triggered through heat treatment because of oxidation. To investigate this phenomenon, we applied heat treatment to our film which resulted in an amplified polarization value and notably improved results. The fabricated composite film was used in tri-layered device consisting of heated BFO-embedded Ti 3 C 2 T x MXene as middle layer that showed excellent data storage capability controlled by ferroelectricity of the middle layer itself. The simultaneous presence of ferroelectric and multiferroic coupling highlights the promising application of MXene-assisted films in data storage applications. [ABSTRACT FROM AUTHOR]

Trends in outpatient dermatology appointment wait times for United States (US) veterans are poorly characterized. Given concerns surrounding prolonged wait times at Veterans Health Administration (VHA) medical facilities, the federal government introduced the Maintaining Internal Systems and Strengthening Outside Networks (MISSION) Act in 2018, allowing veterans to receive VHA-reimbursed community care if VHA specialty care appointments cannot be scheduled within 28 days. Considering this expanded access to community care, we characterized among US veterans the (1) overall demand for dermatology appointments, (2) trends in average wait times, and (3) facility/geographic variation in wait times. The VHA Corporate Data Warehouse was queried for all dermatology appointments from January 1, 2014 to June 30, 2021. Appointment wait time, defined as time from appointment request to completion, was calculated for each care setting: VHA, community, and overall. Linear regression was used to assess average annual changes in wait times, and t-tests were used to compare mean wait times before and after the MISSION Act's implementation in 2018. Median wait times for each facility and state, and the proportion in each category meeting the MISSION Act goal wait time < 28 days, were determined using 2021 data. Our analytic cohort comprised 1,613,262 dermatology appointments directed through 130 VHA facilities. There was a 356% increase in demand for dermatology appointments from 2014 to 2019 (from 85,593 to 296,140 overall visits), with a corresponding 435% increase in demand for community appointments from 2014 to 2020 (from 11.7 to 50.9% of annual visits). Overall appointment wait times increased by an average 0.88 days annually, with community wait times increasing by an annual average of 1.09 days and VHA wait times decreasing by an annual average of 1.01 days (all P < 0.001). In 2021, 35% of VHA facilities and 20% of states had a median appointment wait time < 28 days. We observed an increase in demand over time for outpatient dermatology appointments among US veterans. Appointment wait times increased overall and in community settings, though decreased at VHA facilities. Understanding trends in appointment wait times will help refine policies aimed at increasing dermatologic care access for US veterans. [ABSTRACT FROM AUTHOR]

This paper considers the ways in which research projects linger beyond their ‘official’ endings, and how to deal with this. Building on conversations in human geography and related disciplines on slow research, performed endings, and the practical and socio‐political complexities of data storage and analysis over time, I relate some experiences with my research on the Finnish Saimaa Ringed Seal, which resurfaced years later via a new project. Should I re‐engage or leave it as a discrete period of previous work? An end to funding or finishing the write‐up does not necessarily sever the connection between a researcher and their data. I argue that social research can be an ongoing, slow, and personal process. My aim is to encourage both new and more experienced researchers to reflect on how we think about data and analysis when projects may live on in our minds or in boxes in a cupboard. [ABSTRACT FROM AUTHOR]

In the present paper, we consider the solution of periodic tridiagonal Toeplitz linear systems. By exploiting the special low-rank and Toeplitz structure, we give a new structure-preserving decomposition form of the coefficient matrix. Based on this matrix decomposition form and combined with elementary column operations, we give different algorithms for the fast and reliable solutions of three types of periodic tridiagonal Toeplitz linear systems. Compared with the LU decomposition method, our proposed algorithms take less computational costs and need less memory storage and data transmission. Numerical experiments are given to demonstrate the accuracy and efficiency of our algorithms. All of the experiments are performed on a computer with the aid of programs written in MATLAB. [ABSTRACT FROM AUTHOR]

Analysis of large volume of data is very complex due to not only the high level of skewness and heteroscedasticity of variance but also the difficulty of data storage. Expectile regression is a common alternative method to analyze heterogeneous data. Distributed storage can reduce effectively the storage burden of a single machine. In this paper, we consider fitting linear expectile regression model to estimate conditional expectile based on large-scale data. We store the data in a distributed manner and construct a gradient-enhanced loss (GEL) function as a proxy for the global loss function. A distributed algorithm is proposed for the optimization of the GEL function. The asymptotic properties of the proposed estimator are established. Simulation studies are conducted to assess the finite-sample performance of our proposed estimator. Applications to an analysis of the National Health Interview Survey data set demonstrate the practicability of the proposed method. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to present a novel approach to facial recognition that enhances privacy by using radio frequency identification (RFID) technology combined with transformer models, eliminating the need for visual data and thus reducing privacy risks associated with traditional image-based systems. Design/methodology/approach: The proposed RFID-transformer recognition system (RTRS) uses RFID technology to capture signal features such as phase and received signal strength indicator, which are then processed by a transformer model. The model is specifically designed to handle structured RFID data, capturing subtle patterns and dependencies to achieve accurate biometric recognition. The system's performance was validated through comprehensive experiments involving different environmental conditions and user scenarios. Findings: The experimental results demonstrate that the RTRS system achieves a recognition accuracy of 98.91%, maintaining robust performance across various challenging conditions, including low-light environments and changes in face orientation. In addition, the system provides a high level of privacy preservation by avoiding the collection and storage of visual data. Originality/value: To the best of the authors' knowledge, this work introduces the first RFID-based facial recognition system that fully leverages transformer models, offering a privacy-preserving alternative to traditional image-based methods. The system's ability to perform accurately in diverse scenarios while ensuring user privacy makes it a significant advancement in biometric technology. [ABSTRACT FROM AUTHOR]

Accurately modeling real-world systems requires scientific applications at exascale to generate massive amounts of data and manage data storage efficiently. However, parallel input and output (I/O) faces challenges due to new application workflows and the state-of-the-art memory, interconnect, and storage architectures considered in exascale designs. The storage hierarchy has expanded with node-local persistent memory, solid-state storage, and traditional disk and tape-based storage, thus requiring efficiency at each layer and much more efficient data movement among these layers. This paper discusses how the ExaHDF5 project improved the I/O performance and data management for exascale architectures by enhancing HDF5, a widely used parallel I/O library. The team developed an Asynchronous I/O Virtual Object Layer (VOL) connector that allowed overlapping I/O with computation. They also created a Cache VOL to complement asynchronous I/O by incorporating fast storage layers, such as burst buffer and node-local storage, into the parallel I/O workflow through caching and staging data. Additionally, the team enabled data aggregation and I/O at the node level by using a Subfiling Virtual File Driver (VFD). To demonstrate superior I/O performance with HDF5 at exascale, the ExaHDF5 team collaborated with several exascale applications. In this paper, we show I/O performance improvements for three applications: Cabana (a particle-based simulation library), EQSIM (a regional earthquake simulation software), and E3SM (a climate system modeling library). [ABSTRACT FROM AUTHOR]

Purpose: Advancements in Internet technologies greatly influence digital humanities, yet research investigating web3 (i.e. the blockchain-based, decentralised web) within that domain remains limited. The purpose of this paper is to address that gap, presenting a state-of-the-art synthesis of web3-related technologies for digital humanities infrastructures and exploring associated risks and challenges. Design/methodology/approach: Following a review of the literature, the authors scope out ways blockchain technology, peer-to-peer decentralised storage and other web3 technologies could support digital humanities infrastructures, especially in the context of digital cultural heritage. In this discussion, particular cognisance is given to the needs and aims of the UK's Arts and Humanities Research Council funded Towards a National Collection programme, which seeks to break down the barriers that exist between the UK's cultural heritage collections. Findings: Web3 introduces novel tools and processes that could benefit digital humanities infrastructures, enabling decentralisation and facilitating open access data storage. Yet, significant barriers to adoption remain, such as the requirement for highly specialised technical expertise. Risks and challenges must also be considered prior to any use, including legal, ethical and technical safeguards. Research limitations/implications: This study explores opportunities and risks of web3 for digital humanities, through the lens of digital cultural heritage infrastructures and their requirements, including decentralised storage and persistent identification. It does not provide a holistic overview of all web3 technologies. Practical implications: The authors identify practical uses of web3 technologies for digital humanities projects, outlining potential applications concerning decentralised storage and persistent identification. Originality/value: The authors push forward current knowledge and literature on the intersection of web3 and digital humanities, outlining also practical recommendations for scholars, practitioners and funding organisations. [ABSTRACT FROM AUTHOR]

In recent years, cloud manufacturing has brought both opportunities and challenges to the manufacturing industry. Cloud manufacturing enables global manufacturing resources to be unified and shared, thus breaking down geographical constraints to enhance the level and efficiency of manufacturing. However, with the explosive growth of manufacturing resources and user demands, traditional cloud manufacturing platforms will face problems of insufficient computility, lack of real‐time data and difficulties in securing user privacy during the service selection process. In this article, a blockchain‐based decentralized cloud manufacturing service selection method is proposed, where the computility resource is deployed in multiple distributed nodes rather than the traditional centralized cloud manufacturing platform to solve the problem of insufficient computility. The credibility of the users is evaluated based on their performance on the contract and the PBFT consensus algorithm is improved based on the credibility of the users. In addition, a tri‐chain blockchain data storage model is designed to ensure the security, real‐time and transparency of data in the cloud manufacturing service selection process. The experimental results show that the method both speeds up service selection process and improves the quality of service selection results, and achieves a significant increase in manufacturing efficiency. [ABSTRACT FROM AUTHOR]

With the continuous emergence of modern Internet of Things, mobile Internet and other new generation of campus information technology and its extensive application in professional campus education, the development of college professional campus education information construction has entered a new stage of development. In view of higher requirements on data storage and network transmission delay of core business system in smart campus and more prominent wireless network security problems, this paper proposes a privacy protection protocol for smart campus based on chaotic mapping and edge computing. The protocol uses chaos mapping algorithm to protect user identity and negotiate session keys, and introduces edge computing to process authentication information on the edge server, which reduces the pressure of the core network and improves the authentication efficiency. This paper proves the security of the protocol by using BAN logic and Scyther, and verifies that the protocol can resist known attacks by analysing informal security. Through performance analysis and comparison, the proposed protocol has obvious advantages in computation and communication overhead. [ABSTRACT FROM AUTHOR]

The most important and difficult challenge the digital society has recently faced is ensuring data privacy and security in cloud‐based Internet of Things (IoT) technologies. As a result, many researchers believe that the blockchain's Distributed Ledger Technology (DLT) is a good choice for various clever applications. Nevertheless, it encountered constraints and difficulties with elevated computing expenses, temporal demands, operational intricacy, and diminished security. Therefore, the proposed work aims to develop a Decentralized Identifiable Distributed Ledger Technology‐Blockchain (DIDLT‐BC) framework that is intelligent and effective, requiring the least amount of computing complexity to ensure cloud IoT system safety. In this case, the Rabin algorithm produces the digital signature needed to start the transaction. The public and private keys are then created to verify the transactions. The block is then built using the DIDLT model, which includes the block header information, hash code, timestamp, nonce message, and transaction list. The primary purpose of the Blockchain Consent Algorithm (BCA) is to find solutions for numerous unreliable nodes with varying hash values. The novel contribution of this work is to incorporate the operations of Rabin digital data signature generation, DIDLT‐based blockchain construction, and BCA algorithms for ensuring overall data security in IoT networks. With proper digital signature generation, key generation, blockchain construction and validation operations, secured data storage and retrieval are enabled in the cloud‐IoT systems. By using this integrated DIDLT‐BCA model, the security performance of the proposed system is greatly improved with 98% security, less execution time of up to 150 ms, and reduced mining time of up to 0.98 s. [ABSTRACT FROM AUTHOR]

Hazard-related data are a critical component in construction quality hazard management (CQHM). However, data security and latency issues in CQHM cannot be guaranteed in centralized systems currently and prevent it from achieving the goals of secure and efficient hazard analysis and further real-time quality process control. Focusing on these goals, a decentralized CQHM framework is proposed by introducing blockchain (BC) and deep learning (DL) technology. Moreover, considering the blockchain's limited storage capacity and block size, a deep learning–based multimodal storage strategy is designed with smart contracts and InterPlanetary File System (IPFS) for data lightweight. In accordance with the proposed framework, comparative experiments were conducted to demonstrate its feasibility by analyzing related metrics like accuracy, cost, and throughput. This study deepens the understanding of data security and latency issues in CQHM and offers technical guidance in establishing BC and DL solutions. Besides, the DL-based multimodal storage strategy provides a substantial data-driven advancement for lightweight on-chain data storage. Moreover, the proposed framework is promising to smooth the quality hazard analysis progress in improving on-site decision efficiency, promoting cooperation and standardizing quality process control. [ABSTRACT FROM AUTHOR]

Objective Study Setting and Design Data Sources and Analytic Sample Principal Findings Conclusions To evaluate the effect of enrolling in Supportive Services for Veteran Families (SSVF) on short‐ and long‐term housing outcomes among Veterans experiencing housing instability.We analyzed data from the Department of Veterans Affairs (VA) electronic health record (EHR) between October 2015 and December 2018 using the target trial emulation framework. Veterans were included in one or more trials if they were 18 years or older, had recent evidence of housing instability, had received care in VA for at least 1 year, and had never before enrolled in SSVF. Patients who enrolled in SSVF after meeting eligibility were assigned to the treatment group, while patients who did not enroll in SSVF were assigned to a control group. We extracted patients' housing outcomes from the EHR and modeled the probability of being unstably housed each day while accounting for confounders and irregular visit times.We extracted housing status and covariates from the VA Corporate Data Warehouse. Housing instability was ascertained using a combination of structured data elements and natural language processing.We identified 238,059 unique patients who met the eligibility criteria for one or more trials. The risk of housing instability decreased in both arms over the three years after initiating a trial but was lower among SSVF enrollees, with a risk difference of −12.9% (95% confidence band −14.6%, −11.2%) on Day 120 and an attenuated difference of −2.4% (−4.0%, −0.7%) on Day 1095.SSVF is one of the largest rapid rehousing and homelessness prevention programs in the nation. We found that SSVF improves housing outcomes over the three years following enrollment, but the effect reduces over time. These findings can inform policy and program design for improving housing outcomes for homeless‐experienced individuals. [ABSTRACT FROM AUTHOR]

Diarylethenes (DAEs) are typical photochemically reversible type (P‐type) photochromic materials with excellent thermal stability and high fatigue resistance and are widely exploited as photo‐switches for various applications in molecular devices, data storage, photoresponsive materials, and bioimaging, etc. In recent years, there is an increasing number of reports using heat, acid, electrochemistry, etc. to drive the isomerization reaction of DAEs. The response to two or more different stimuli enables multi‐functionality within a single DAE molecule, which would facilitate complex logic‐gate operations, multimode data storage, and increased information density. Herein, the recent advances in DAE systems utilizing stimuli "beyond photo" to trigger the isomerization processes from three perspectives: acidochromism, thermochromism, and electrochromism are reviewed. Emphasis is placed on the molecule design strategies and the underlying mechanisms for cyclization and cycloreversion processes addressed by the alternative stimulus. Then the noticeable applications made in multi‐stimuli responsive DAE systems are summarized. Additionally, the challenges and opportunities of DAE switches driven by stimuli "beyond photo" in the future are also discussed. [ABSTRACT FROM AUTHOR]

This research reports the results of an experimental and numerical analysis of the La 0.9 Ce 0.1 Ni 5 alloy's hydrogen absorption and desorption isotherms at three distinct temperatures (T = 313 K, 333 K, and 353 K). We first determined the morphological and structural properties, as well as the hydrogen storage isotherms, of the intermetallic La 0.9 Ce 0.1 Ni 5 experimentally. The experimental isotherms were then compared to a mathematical model based on statistical physical theory. Due to the good agreement between the experimental isotherms and the proposed model, the insertion and release of hydrogen atoms (n α , n β), geometric densities of receptor sites (N αm , N βm), and absorption-desorption energies (P α , P β) were determined. Moreover, thermodynamic functions like enthalpy, entropy, Gibbs free energy, and internal energy were calculated using these parameters. The findings demonstrated that the intermetallic compound's CaCu 5 structure promotes the formation of stable metal hydrides through attractive interactions, ensuring that hydrogen atoms are securely trapped in the metal lattice, thereby enhancing the material's hydrogen storage capacity. • The suggested alloy isotherms were determined experimentally at various temperatures. • A numerical model has been developed to adjust the experimental data of hydrogen storage by the La 0.9 Ce 0.1 Ni 5 alloy. • The numerical and experimental results demonstrate a good agreement. [ABSTRACT FROM AUTHOR]

With the continuous development of network technology, cryptographic protocols are facing diverse and complex security challenges. Blockchain technology, as a solution incorporating decentralization, traceability, programmability, and immutability, effectively enhances the security, trustworthiness, operational efficiency, and ensures the security and integrity of data storage in traditional cryptographic protocols. Consequently, it has gradually emerged as a focal point of research in cryptographic protocols. This manuscript delves into the ongoing research concerning the application of blockchain technology in cryptographic protocols. First, this manuscript introduces the background of blockchain research in cryptographic protocols and the corresponding basic knowledge. Secondly, we delve into the main concerns of traditional cryptographic protocols, with a particular focus on security and performance. Thirdly, according to the main classification of cryptographic protocols, the latest research results of blockchain in authentication protocols, authentication and key agreement protocols, and e-commerce protocols are presented. Finally, the research directions of blockchain technology in cryptographic protocols are summarized based on the existing research, and the future development trend is also prospected. [ABSTRACT FROM AUTHOR]

Iron germanide (FeGe) emerges as a promising magnetic alloy for spintronics and high-density data storage, owing to its distinctive magnetic properties and compatibility with existing fabrication techniques. This compatibility enables the synthesis of customized FeGe nanocylinders characterized by chirality, where their magnetization asymmetrically twists. Within specific size parameters, these nanocylinders can accommodate skyrmions—swirling magnetic structures with significant implications for information storage and processing technologies. This study investigates the response of FeGe nanocylinders to external magnetic fields, focusing on how their magnetic properties vary with dimensions (diameter and length). Specifically, we analyze the impact of length on the pseudo-static properties of short FeGe nanocylinders and examine the average topological charge and remanence states across different aspect ratios. Our investigation underscores the relationship between chirality and diverse magnetization states in four types of nanocylinders with varying aspect ratios. This comprehensive analysis elucidates the connection between nanocylinder magnetic states and the average topological charge—a critical factor in advancing ultra-low-energy data storage and logic devices. [ABSTRACT FROM AUTHOR]

Summary: The precise diagnosis and effective treatment of patients rely heavily on healthcare data. However, sharing healthcare information can be challenging due to the potential risks of unauthorized tampering and data leakage. To address these concerns and facilitate secure and efficient data access for stakeholders within and outside the healthcare system, this study introduces a patient‐enabled blockchain system (PEBS). Patient‐enabled blockchain system uses the Model View Controller (MVC) approach where the model manages the off‐chain and on‐chain data, the view is the user‐accessible module, and the controller acts as an interface between a user interface and storage layer. It enables patients to control their data by determining specific access permissions and executes various smart contracts for stakeholders' registration, authorization, data storage, query, and update operations. Patient‐enabled blockchain system incorporates Modified Proof‐of‐Authority (MPoA), which has been compared against various consensus algorithms such as Proof‐of‐Work (PoW), Proof‐of‐Authority (PoA), and Istanbul Byzantine Fault Tolerance (IBFT). Furthermore, the suggested system incorporates the utilization of the Interplanetary File System (IPFS) to address concerns related to performance and storage. We conducted an in‐depth analysis and comparison of the system's performance using key parameters such as transaction latency and throughput. Experiments are carried out using network sizes of 10 and 30, with transaction counts from 5 to 500. The experiments show that the highest latency for the proposed system is 58,105 ms, almost 4.8 times less than PoW, which is 283,575 and provides 2.7 times higher throughput (101 transactions per second) than PoW (38 transactions per second). [ABSTRACT FROM AUTHOR]

Taking Luliang County, Qujing City, Yunnan Province as an example, the spatial and temporal distribution data of carbon storage in the study area were obtained through five periods of land use data and carbon density data in 2000, 2005, 2010, 2015 and 2020. The carbon stor- age module of GIS and InVEST was used to analyze the characteristics of carbon storage changes in Luliang County in the past 20 years. The re- sults showed that over the 20-year period, the area of cultivated land and forest land had slightly decreased, while the grassland area had de- creased significantly, and the areas of water bodies and construction land had increased significantly, with unused land decreasing noticeably. The overall carbon storage showed a declining trend, especially during the period from 2015 to 2020, which was consistent with changes in land use. There were significant differences in carbon storage changes among different land types, with forest land having the highest average carbon storage, while construction land, waters and unused land had relatively low average carbon storage. The spatial distribution of carbon storage had not changed significantly, high-value areas mainly distributed in forest areas, and low-value areas mainly distributed in construction land and cultivated land concentration areas. In summary, there was a close correlation between land use change and carbon storage change. Factors such as urbanization and reduced cultivated land may lead to a decrease in carbon storage, while measures such as protecting forests and wetlands may help maintain or increase carbon storage. [ABSTRACT FROM AUTHOR]

As terahertz (THz) technology has been widely considered as a key candidate for future sixth‐generation wireless communication networks, THz modulators show profound significance in wireless communication, data storage, and imaging. In special, dynamic tuning of THz waves through 2D electron gas (2DEG) incorporated with a hybrid design of metasurface has attracted keen interest due to the combined merits of deliberate structural design, rapid switching speed and the process compatibility. Current meta‐modulator enables very high modulation depth but encounter limited bandwidth. In this paper, by taking into account the co‐functional effects of temperature and voltage‐dependent dynamic control on transmission amplitude, a 2DEG‐based GaN‐on‐Si modulator with two switchable operational states (or four modes) of active wave control is proposed. Under cryogenic temperature conditions, the proposed device exhibits prominent 2D plasmons characteristics with switchable transitions between the gated mode and ungated mode for active control. Under room temperature conditions, the proposed device exhibits non‐resonance broadband spectra characteristics with tunable transitions between the linearity mode and depletion mode for transmission control. The scheme provides an option for the development of the actively tunable THz meta‐modulator and paves a way for the robust multifunctionality of electrically controllable THz switching, and biosensors. [ABSTRACT FROM AUTHOR]

Aims Methods Results Conclusions Recording the indication for a medicine in the prescription supports communication. In May 2023, our district hospitals made the free‐text indication field in prescriptions compulsory for all medicines in the inpatient prescribing system. This study aimed to evaluate the effect of introducing a compulsory indication field in an inpatient prescribing system.Text in the indication field was manually classified as an indication, ‘other text’, ‘rubbish text’, ‘to be determined’ and ‘blank’. Prescribing data were extracted from the district data warehouse. The change in proportion of prescriptions with an indication was compared for 8 weeks after introduction of a compulsory indication field to an equivalent 8 weeks in 2022. Secondary outcomes included medication cessation and indication recording before discharge.We analysed 81 634 prescriptions before and 82 726 after indications were made compulsory. The proportion of prescriptions with an indication increased from 29.2% to 75.6%. ‘Rubbish text’ increased from 0% to 2.3%, ‘other text’ from 2.5% to 14.7%, and ‘to be determined’ from 0.0% to 6.6%. Of 5557 prescriptions with ‘to be determined’ initially, 18.1% were ceased and 2.7% had an indication before discharge.After making the prescription indication field compulsory, the proportion of medicines with an indication increased from 29% to 76%, with only a small increase in ‘rubbish text’. Following the system change, the quality of information recording improved but there was no change in medicine use. Compulsory fields should be combined with improvements in other components of care to improve medicine use. [ABSTRACT FROM AUTHOR]

In recent years, the growth of digital data has been unimaginable. This also applies to geospatial data. One of the largest data types is LiDAR point clouds. Their large volumes on disk, both at the acquisition and processing stages, and in the final versions translate into a high demand for disk space and therefore electricity. It is therefore obvious that in order to reduce energy consumption, lower the carbon footprint of the activity and sensitize sustainability in the digitization of the industry, lossless compression of the aforementioned datasets is a good solution. In this article, a new format for point clouds—3DL—is presented, the effectiveness of which is compared with 21 available formats that can contain LiDAR data. A total of 404 processes were carried out to validate the 3DL file format. The validation was based on four LiDAR point clouds stored in LAS files: two files derived from ALS (airborne laser scanning), one in the local coordinate system and the other in PL-2000; and two obtained by TLS (terrestrial laser scanning), also with the same georeferencing (local and national PL-2000). During research, each LAS file was saved 101 different ways in 22 different formats, and the results were then compared in several ways (according to the coordinate system, ALS and TLS data, both types of data within a single coordinate system and the time of processing). The validated solution (3DL) achieved CR (compression rate) results of around 32% for ALS data and around 42% for TLS data, while the best solutions reached 15% for ALS and 34% for TLS. On the other hand, the worst method compressed the file up to 424.92% (ALS_PL2000). This significant reduction in file size contributes to a significant reduction in energy consumption during the storage of LiDAR point clouds, their transmission over the internet and/or during copy/transfer. For all solutions, rankings were developed according to CR and CT (compression time) parameters. [ABSTRACT FROM AUTHOR]

2D ferroelectric materials present promising applications in information storage, sensor technology, and optoelectronics through their coupling with magnetics/valleytronics, mechanics, and optics, respectively. The integration of 2D ferroelectrics with magnetism enhances data storage density in memory devices by enabling electric‐field‐controlled magnetic states. Ferroelectric‐valley coupling holds promise for high‐speed, low‐energy electronics by leveraging the electrical control of valley polarization. Ferroelectric‐strain coupling results in various polar topologies, with potential applications in high‐density data storage technologies and sensor devices. Moreover, the coupling between ferroelectrics and optics facilitates the development of nonlinear photonics based on ferroelectric materials. This review summarizes the latest theoretical progress in the coupling mechanisms, including the Dzyaloshinskii‐Moriya‐interaction‐induced magnetoelectric coupling, symmetry‐linked ferroelectric‐valley coupling, ferroelectric‐strain‐coupling‐generated polar topologies, and second‐harmonic generation through ferroelectric‐light interactions. The current challenges and future opportunities in harnessing the coupling in 2D ferroelectric materials for multifunctional applications are provided. [ABSTRACT FROM AUTHOR]

ABSTRACT Phenotypic trait identification is crucial in cultivating new soybean varieties with high yield and quality. The traditional soybean phenotypic trait identification relies on manual pod counting and plant height measuring with a ruler. The heavy workload causes the data collected by human resources to be extremely prone to error. Therefore, developing an efficient and high‐quality method to obtain phenotypic data of soybean pods and branches is urgently needed. Three network models including ResNet‐101, Swin‐S and ConvNeXt‐S are compared in this study, and the ConvNeXt‐S model is identified as optimal, with a mAP@0.5 of 0.95, which could reach 74.2%. A deep learning–based approach soybean plant phenotype detection and data storage system is developed, including information on plants, pods and branches. The R2 between the number of pods detected by the system and the true value reached 0.995. These results indicate that the system is more accurate and stable than the manual phenotype identification. Our study paves the way for reducing economic and time costs as well as improving phenotype identification efficiency and accuracy in detecting soybean phenotypes. [ABSTRACT FROM AUTHOR]

It is always a hot and difficult problem of how to realize multi-bit data storage by preparing multi-resistance memristors by a simple process compatible with standard CMOS processes. In this work, a tristable TaO x -based memristor with tunable oxygen vacancies is fabricated by physical vapor deposition, consisting of a high-resistance state and two low-resistance states. Its set and reset voltages are low −1.1V, −2.1V, and -1V, 3.3V, respectively. The XPS characterization demonstrates the presence of three valence states within the TaO x film. It has been suggested that different barriers lead to different switching voltages during the transition of the trivalent state, resulting in the formation of stable states. Interestingly, when increasing the concentration of oxygen during preparation to decrease the concentration of oxygen vacancies in TaO x film, the volt-ampere properties of memristor change from tristable to bistable, which further proves the above point. This work provides a viable strategy for switching between bistable and tristable states in memristors prepared from transition metal oxides. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has become a pervasive phenomenon, with applications in a multitude of sectors, including healthcare, smart agriculture, smart cities, transportation, and water management. This has led to a significant generation of Big Data. In order to process this substantial volume of data efficiently, there is a pressing need for a platform capable of handling large quantities. However, real-time applications face challenges in cloud processing due to high latency. As a complementary infrastructure to the cloud, fog computing emerges as a viable solution by facilitating task processing, networking, and data storage in cloud data centers accessible to mobile users. The offloading of tasks represents a promising solution to the resource constraints inherent in IoT applications, particularly within the context of fog computing. This process entails the execution of particular components of mobile applications within a fog–cloud environment, to reduce execution time and energy consumption. The objective of our research is to optimize task offloading in IoT within heterogeneous environments, taking into account conflicting constraints. This optimization challenge is formulated as a multi-objective problem, with a particular focus on energy consumption and latency, as well as quality of service metrics. The proposed solution, TOF-NSGAII, is designed to respect the finite resources of fog computing, balancing workloads to meet the latency requirements of IoT tasks. The widely employed meta-heuristic, the non-dominated sorting genetic algorithm (NSGA-II), has been adapted to generate a set of non-dominated multi-objective task offloading optimization solutions, considering both energy consumption and latency. The experimental results demonstrate the efficacy of TOF-NSGAII in generating task offloading solutions that distribute executed tasks between fog and cloud computing environments in a judicious manner, based on their specific requirements. Furthermore, the generated non-dominated solutions demonstrate optimality in terms of energy consumption, with an average reduction of 12.18% compared to alternative approaches. It is noteworthy that our approach introduces only a marginal increase in latency, amounting to 0.38%, which can be considered negligible. [ABSTRACT FROM AUTHOR]

The growing popularity of the most current wave of decentralized systems, powered by blockchain technology, which act as data vaults and preserve data, ensures that, once stored, it stays preserved, considered to be one of the most promising safe and immutable storage methods. The authors of this research suggest an on-chain storage framework that stores files inside blockchain transactions using file transforming, chunking, and encoding techniques. This study investigates the performance of on-chain file storage using a simulated network blockchain environment. Test files of varying sizes were deployed. Performance metrics, including consumed time in chunking, encoding, and distributing chunks among block transactions, were measured and analyzed. An analysis of the collected data was conducted to assess the framework's performance. The result showed that selecting the appropriate chunk size significantly influences the overall performance of the system. We also explored the implications of our findings and offered suggestions for improving performance within the framework. [ABSTRACT FROM AUTHOR]

Data storage on DNA has emerged as a molecular approach to safeguarding digital information. Microarrays are an excellent source of complex DNA sequence libraries and are playing a central role in the development of this technology. However, the amount of DNA recovered from microarrays is often too small, and a PCR amplification step is usually required. Primer information can be conveyed alongside the DNA library itself in the form of readable barcodes made of DNA on the array surface. Here, we present a synthetic method to pattern QR and data matrix barcodes using DNA photolithography, phosphoramidite chemistry and fluorescent labeling. Patterning and DNA library synthesis occur simultaneously and on the same surface. We manipulate the chemical composition of the barcodes to make them indelible, erasable or hidden, and a simple chemical treatment under basic conditions can reveal or degrade the pattern. In doing so, information crucial to retrieval and amplification can be made available by the user at the appropriate stage. The code and its data contained within are intimately linked to the library as they are synthesized simultaneously and on the same surface. This process is, in principle, applicable to any in situ microarray synthesis method, for instance, inkjet or electrochemical DNA synthesis. [ABSTRACT FROM AUTHOR]

Purpose: This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation challenges, so interest in its impact on operational performance has grown steadily over the last few years. Design/methodology/approach: Drawing on transaction cost economics and the contingency theory, we built a set of hypotheses. These were tested through a long-term event study and an ordinary least squares regression involving 130 adopters listed in North America. Findings: Compared with the control sample, adopters displayed significant abnormal performance in terms of labor productivity, operating cycle and profitability, whereas sales appeared unaffected. Firms in regulated settings and closer to the end customer showed more positive effects. Neither industry-level competition nor the early involvement of a project partner emerged as relevant contextual factors. Originality/value: This research presents the first extensive analysis of operational performance based on objective measures. In contrast to previous studies and theoretical predictions, the results indicate that blockchain adoption is not associated with sales improvement. This can be explained considering that secure data storage and sharing do not guarantee the factual credibility of recorded data, which needs to be proved to customers in alternative ways. Conversely, improvements in other operational performance dimensions confirm that blockchain can support inter-organizational transactions more efficiently. The results are relevant in times when, following hype, there are signs of disengagement with the technology. [ABSTRACT FROM AUTHOR]

Non‐trivial relationships link individual materials properties to device‐level performance. Device optimization therefore calls for new automation approaches beyond the laboratory bench with tight integration of different research methods. This study demonstrates a Materials Acceleration Platform (MAP) in the field of battery research based on the problem‐agnostic Fast INtention‐Agnostic LEarning Server (FINALES) framework, which integrates simulations and physical experiments while leaving the active control of the hardware and software resources executing experiments or simulations with the partners running the respective units. This decentralization of control is a distinctive feature of MAPs using the FINALES framework. The connected capabilities entail the formulation and characterization of electrolytes, cell assembly and testing, early lifetime prediction, and ontology‐mapped data storage provided by institutions distributed across Europe. The infrastructure is used to optimize the ionic conductivity of electrolytes and the End Of Life (EOL) of lithium‐ion coin cells by varying the electrolyte formulation. Trends in ionic conductivity are rediscovered and the effect of the electrolyte formulation on the EOL is investigated. Further, the capability of this MAP to bridge diverse research modalities, scales, and institutions enabling system‐level investigations under asynchronous conditions while handling concurrent workflows on the material‐ and system‐level is shown, demonstrating true intention‐agnosticism. [ABSTRACT FROM AUTHOR]

Circularly polarized luminescence (CPL) has attracted tremendous attention because of its significant application prospect across multiple fields of three‐dimensional display, data storage, and information encryption. Chirality and luminescence are two necessary prerequisites for the generation of CPL. However, controlling these two factors simultaneously in a rational manner remains a challenge. Herein, we highlight the recent advances on the rational generation and regulation of CPL through the new concept, named matching rules, mainly including fluorescence‐selective absorption, circularly polarized fluorescence energy transfer, and chiral communication between excited state and ground state. An important commonality among these strategies is that they need a good overlap of the corresponding spectra between the luminescent part (fluorescence, phosphorescence, or CPL) and the chiral part (organic, inorganic, or organic‐inorganic hybrid materials), which can be contactless and separate. Different from most previous studies, no covalent or noncovalent interactions between the two parts are required, which makes them more facile and convenient. Finally, we summarize the main advantages of these strategies and the current challenges. We expect this concept to offer insightful and novel understanding and inspiration on CPL generation and regulation. [ABSTRACT FROM AUTHOR]

Metasurfaces garner widespread attention for their remarkable ability to precisely manipulate light and construct optical multiplexing devices. However, there is still a lack of effective solutions for achieving high‐performance wavelength decoupling in the realm of wavelength multiplexing. In this work, a novel wavelength decoupling method based on minimalist metasurfaces featuring a single‐celled configuration is proposed. These metasurfaces are composed of only two types of nanobricks, each capable of modulating the phase of two different wavelengths simultaneously as desired. The proposed minimalist metasurfaces possess the advantages of flexible design, enabling wavelength decoupling with incidences at both co‐ and cross‐polarization states. Interestingly, by integrating the wavelength decoupling metasurface with liquid crystal devices, information encryption can be achieved. The proposed wavelength decoupling method holds broad application prospects in the fields of optical data storage, image display, information security, and beyond. [ABSTRACT FROM AUTHOR]

Supramolecular condensation during cooling cycles often transitions through multiple metastable phases before achieving a stable crystalline state. Metastability arises from various competing parameters like symmetrical arrangement, and supramolecular bonding and manifests at different temperatures. Symmetrical physical arrangements can minimize vibrational energy and stabilize the systems at higher temperatures. Further cooling promotes directional supramolecular bonding, such as charge‐assisted hydrogen bonding, resulting in molecular periodicity within metastable structures. Frustration occurs when weaker van der Waals bonds form during further cooling, propagating perpendicularly to stronger one‐dimensional charge‐assisted hydrogen bonds and disrupting lateral periodicity in certain solvents. This makes parallel 1D fibers slidable, adding flexibility to the gel fiber. Eventually, some supramolecular systems attain thermodynamically stable crystalline states by perfectly arranging all the molecules. Throughout the process, metastability results from different symmetrical arrangements, and each rearrangement alters the supramolecular structure‘s symmetry, generating new physicochemical properties. Different supramolecular gels uniquely break symmetry, which can be monitored through various techniques. This perspective analyzes supramolecular thermoreversible, reverse thermal, liquid crystalline, thixotropic, and antisolvent‐induced gels to illustrate spontaneous symmetry reduction processes. Reaching a suprasymmetry condensate can classify big data and be applied in unconventional analogue computing or data storage. [ABSTRACT FROM AUTHOR]

With the growing need for extensive data storage, enhancing the storage density of nonvolatile memory technologies presents a significant challenge for commercial applications. This study explores the use of monatomic antimony (Sb) in multi-level phase-change storage, leveraging its thickness-dependent crystallization behavior. We optimized nanoscale Sb films capped with a 4-nm SiO2 layer, which exhibit excellent amorphous thermal stability. The crystallization temperature ranges from 165 to 245 °C as the film thickness decreases from 5 to 3 nm. These optimized films were then assembled into a multilayer structure to achieve multi-level phase-change storage. A typical multilayer film consisting of three Sb layers was fabricated as phase-change random access memory (PCRAM), demonstrating four distinct resistance states with a large on/off ratio (∼102) and significant variation in operation voltage (∼0.5 V). This rapid, reversible, and low-energy multi-level storage was achieved using an electrical pulse as short as 20 ns at low voltages of 1.0, 2.1, 3.0, and 3.6 V for the first, second, and third SET operation, and RESET operation, respectively. The multi-level storage capability, enabled by segregation-free Sb with enhanced thermal stability through nano-confinement effects, offers a promising pathway toward high-density PCRAM suitable for large-scale neuromorphic computing. [ABSTRACT FROM AUTHOR]

ABSTRACT This article proposes a comprehensive analysis of architectures that use blockchain technology to solve important aspects of computing sustainability, with an emphasis on scalability, resource utilization, transparency, and energy conservation. The research focuses on analyzing various structure which embraces decentralization and consensus principles, to redefine the computer infrastructure environment. The study highlights the technology that aids in improving scalability and resource utilization by decentralizing data storage and processing, relieving the load on centralized servers, and lowering the environmental effect of large‐scale data centers. This study's findings are significant in uncovering best practices and optimizing the environmental impact of blockchain technology by evaluating blockchain indicators such as scalability, resource utilization, transparency, and energy saving within the framework of sustainable computing. The project intends to assist in the development of resource‐efficient solutions, address scalability issues, and promote openness and accountability by evaluating the performance of various blockchain implementations. The findings help to promote the larger goal of connecting technical improvements, notably in blockchain, with global environmental goals. The research reveals that energy conservation is an important aspect of sustainability, and the different frameworks including techniques for optimizing energy consumption based on carbon footprint concerns, decentralization, and consensus methods are intended to prioritize energy‐efficient nodes and promote environmentally friendly practices, resulting in a greener computing ecosystem. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusions The widespread adoption of knowledge‐based planning in radiation oncology clinics is hindered by the lack of data and the difficulty associated with sharing medical data.This study aims to assess the feasibility of mitigating this challenge through federated learning (FL): a centralized model trained with distributed datasets, while keeping data localized and private.This concept was tested using 273 prostate 45 Gy plans. The cases were split into a training set with 220 cases and a validation set with 53 cases. The training set was further separated into 10 subsets to simulate treatment plans from different clinics. A gradient‐boosting model was used to predict bladder and rectum V30Gy, V35Gy, and V40Gy. The Federated Averaging algorithm was employed to aggregate the individual model weights from distributed datasets. Grid search with five‐fold in‐training‐set cross‐validation was implemented to tune model hyperparameters. Additionally, we evaluated the robustness of the FL approach by varying the distribution of the training set data in several scenarios, including different number of sites and imbalanced data across sites.The mean absolute error (MAE) for the FL model (4.7% ± 2.9%) is significantly lower than individual models trained separately (6.5% ± 4.9%, p < 0.001) and similar to a traditional centralized model (4.4% ± 2.8%, p = 0.14). The federated model is robust to the number of subsets, showing MAE of 4.7% ± 3.2%, 4.8% ± 3.1%, 4.8% ± 2.9%, 4.5% ± 2.8%, 4.9% ± 3.3%, and 4.8% ± 3.1% for 5, 10, 15, 20, 25, and 30 subsets, respectively. For the two imbalanced datasets, the FL model achieves MAEs of 4.5% ± 2.9% and 5.6% ± 4.0%, non‐inferior to the balanced data model. For all bladder and rectum metrics, the FL model significantly outperforms 36.7% of individual models.This study demonstrates the potential advantages of implementing a federated model over training individual models: the proposed FL approach achieves similar prediction accuracy as a conventional model without requiring centralized data storage. Even when local models struggle to produce accurate predictions due to data scarcity, the federated model consistently maintains high performance. [ABSTRACT FROM AUTHOR]

This research investigates the development of a digital twin (DT) for ground heat exchangers (GHEs) and its potential to enhance the efficiency and sustainability of shallow geothermal energy systems. It introduces an innovative approach for building a GHE‐DT that connects the physical and digital systems to monitor key parameters, predict issues, and optimize energy efficiency. The process involves several phases including implicit knowledge codification, data‐driven analysis, model construction, and system design. The study emphasizes real‐time monitoring of the effective parameters: ground temperature and fluid conditions (flow rate, temperature, and pressure). The GHE‐DT's digital system mainly comprises three sections, namely, data storage, mathematical modeling, and data‐driven modeling. The role of the presented mathematical model is to simulate the GHE's behavior and assess its performance characteristics, such as the heat exchanger's effectiveness and efficiency. Additionally, the data‐driven model used in the proposed DT utilizes formal concept analysis and relation concept analysis to identify connections and associations among parameters for a better understanding of the GHE functioning. The GHE‐DT provides useful services including trend analysis, problem prediction, and correlation analysis. These services provide engineers and operators with the opportunity to increase dependability, save maintenance costs, and optimize GHE performance. [ABSTRACT FROM AUTHOR]

Optically stimulated luminescence (OSL) materials hold great potential for optical data storage (ODS) and anticounterfeiting applications. Nevertheless, the scarcity of suitable luminescent materials with deep‐level traps remains a significant obstacle. Herein, a host substation strategy have been employed to tune the persistent luminescence (PersL) and OSL properties of Ca3Ga4O9:Tb3+ by Al3+ substitution through trap engineering and demonstrated their potential. Specifically, the photoluminescence of the Ca2.985(Ga1‐y%Aly%)4O9:0.5%Tb3+ of Tb3+ is first investigated due to its different occupancies of Ca2+. The influence of host substitution on the crystal structure, trap depth, trap density, PersL, and OSL properties have further investigated. A series of strong PersL and OSL peaks from the Ca2.985(Ga1‐y%Aly%)4O9:0.5%Tb3+ with bluish‐green emissions have been observed. The Ca2.985(Ga1‐y%Aly%)4O9:0.5%Tb3+ have shown controllable photon release upon thermal and optical stimuli, enhancing their performance for ODS. Thermally stimulated luminescence suggests that vacancy and defect concentrations inside the Ca3‐x%(Ga1‐y%Aly%)4O9:x%Tb3+ can be manipulated by Tb3+ doping and Al3+ substitution, which ultimately leads to the formation of deep traps and a broad distribution of traps with increased deep trap concentration. The work demonstrates that trap engineering through Al3⁺ substitution is an effective method for tuning PersL and OSL properties of Ca2.985(Ga1‐y%Aly%)4O9:0.5%Tb3+ for ODS. [ABSTRACT FROM AUTHOR]

Non‐volatile photomemory based on photomodulated luminescent materials offers unique advantages over voltage‐driven memory, including low residual crosstalk and high storage speed. However, conventional materials have thus far been volatile and insecure for data storage because of low trap depth and single‐level storage channels. Therefore, the development of a novel non‐volatile multilevel storage medium for data encryption remains a challenge. Herein, a robust, non‐volatile, multilevel optical storage medium is reported, based on a photomodulated Ba3MgSi2O8:Eu3+, which combined the merits of light‐induced valence (Eu3+ → Eu2+) and photochromic phenomena using optical stimulation effects, accompanied by larger luminescent and color contrasts (>90%). These two unique features provided dual‐level storage channels in a single host, significantly improving the data storage security. Notably, dual‐level optical signals could be written and erased simultaneously by alternating 265 and 365 nm light stimuli. Theoretical calculations indicated that robust color centers induced by intrinsic interstitial Mg and vacancy defects with suitable trap depths enable excellent reversibility and long‐term storage capability. By relying on different luminescent readout mechanisms, the encrypted dual‐level information can be accurately decrypted by separately probing the Eu2+ and Eu3+ signals, thus ensuring information security. This study proposes a novel approach for constructing multilevel information storage channels for information security. [ABSTRACT FROM AUTHOR]

Sonneratia apetala, a nutrient-rich mangrove fruit, presents an opportunity for innovative food product development, offering potential health benefits and economic value through the creation of jam, jelly, and pickle. This innovative invention reveals the nutritional content including vitamins and minerals of Sonneratia apetala jam, jelly, and pickles from Nijhum Dwip in Hatiya Upazila, Noakhali District. These products contain Na, Mg, K, Ca, Mn, Fe, Cu, and Zn, which are essential for human nutrition. The texture and sensory qualities of the products depend on their Total Soluble Solids (TSS), acidity, moisture, pH, and total sugar content, with each parameter receiving an average score of 7 to 8 out of 9 (hedonic scale). Trace amounts of Cd, Cr, Pb, and Hg were found to be significantly below the safe consumption limits. F-, Cl-, SO42-, soluble and total PO43- concentrations were also below safety thresholds. The moisture, ash, protein, fat, fiber, pectin, sugar, carbohydrate, and caloric values highlight the dietary benefits and energy content of these products. The products exhibited higher levels of vitamin C and minerals compared to other citrus fruits. All tested parameters met safe consumption standards, ensuring product safety. These products underwent testing for Heterotrophic Bacterial Count to guarantee their safety. A one-year shelf life is ensured by conducting quarterly storage data checks and organoleptic tests by a 10-member jury panel. The one-way ANOVA test for sensory analysis and shelf life detection indicates statistically significant results. These products help mitigate nutrient deficiencies and promote health by regulating the diet. Applying this technology in grassroots jam, jelly, and pickle production could potentially boost the local economy by approximately $10,000 annually through the creation of small industries among the coastal population. [ABSTRACT FROM AUTHOR]

Wound trajectory and outcomes research has applications in different aspects of wound healing: forecasting wound healing time, access and utilization of wound care services, factors associated with disparities in wound care services, and its quality and outcomes. Wound care research benefits from a well-maintained record management system. In this article, we demonstrate the customization of the District Health Information Software (DHIS2) platform to integrate wound care clinical data with social determinants of health from several Comprehensive Wound Centers (CWC) in Indiana. We describe the modules and features of our platform, such as tracker capture, visualization, and maps. DHIS2 is used in more than 60 countries to monitor and evaluate health programs. However, to the best of our knowledge, this is the first attempt to use DHIS2 as a wound care data warehouse, a platform to perform wound care research for academic researchers and clinical practitioners. Clinicians can use the platform as one of the key tools to make an informed decision in determining the treatment for favorable healing trajectory and wound outcomes. We conducted a usability and acceptance survey among researchers at the Indiana Center for Regenerative Medicine and Engineering and found that DHIS2 can be a suitable infrastructure to manage metadata to import and analyze combined data from disparate sources, including Electronic Medical Records, WoundExpert, and clinical trials management software like REDCap. [ABSTRACT FROM AUTHOR]